As we dive deeper into our HR technology AI blog series, we speak with Alex Miklin, Senior Vice President of Industry and Technology Solutions, about the challenges in implementing AI into HR.
Challenges in Implementing AI and Automation in HR
While AI continues to evolve, it’s far from a perfected technology. Adoption is an important part of its growth, but that comes largely from the knowledge that there will be challenges and HR teams will have to devise workable solutions.
Data Privacy and Security Concerns
AI’s reliance on vast data troves raises serious privacy concerns. Collection of personal information for training models risks breaches, surveillance, and misuse. Additionally, the lack of transparency in algorithms may amplify biases, affecting decision-making. That’s why striking a balance between innovation and safeguarding privacy is crucial to fostering trust and ethical AI deployment.
“Security is a pretty critical component whenever you’re leveraging your customer’s data in a third-party AI,” Miklin says. “You have to have the right data governance policies in place to ensure your customers’ data is secured.”
Early Adoption and Reliance
“Many companies have jumped the gun on AI, whether it’s automated recommendations based on data or other use cases. It seems like some companies have decided that this is a necessity before fully flushing out what the outcomes are trying to achieve,” Miklin says.
For companies exploring AI possibilities or those already integrating it into their daily operations, consider its adoption a marathon rather than a sprint. AI and automation should be an added support rather than a sole focus.
“You could have a company that has let go of some of their workforce because they believe they can automate some of those tasks via AI technologies,” Miklin says. “Worst case scenario, you have business units that are no longer operating effectively because they’ve become so reliant… But I think we’re a long way away from that, at least within the HR tech space.”
Integration and Compatibility
Integrating AI and automation into HR systems takes time and careful planning. Challenges like compatibility issues and employee resistance are likely to arise, but how can these be addressed effectively? In Miklin’s view, testing and stakeholder involvement are key.
“It’s a combination of understanding the parameters that you need to provide to any large language model (LLM) in order to be able to operate it effectively,” Miklin says. “Also identifying through leadership: what are the outcomes that you want to solve for in using an AI? And then driving a tactical strategy within your HR team and your employee workforce.”
Integrating AI into HR comes with hurdles like data privacy and adoption complexities. Balancing innovation and privacy is key. Success demands careful planning, stakeholder involvement, and outcome-driven strategies. Delve deeper into HRSoft’s opinion of AI’s impact on HR software.